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CAIML #39 is going to happen on November 4, 2025, at REWE digital GmbH.

We will have two talks with additional time for networking.

Talk 1: Juri Wiens (AI Research Engineer at REWE digital): One Voice, Many Minds: Engineering Voice-First Multi-Agent Systems

In settings where hands are busy, voice first agentic systems promise autonomous, goal oriented assistance and often need to scale as distributed multi agent architectures for extensibility, including remote agents. There is an option space, but this talk focuses on real time APIs backed by speech to speech models. We show how stateful, bidirectional audio shapes latency budgets, session state, observability, and orchestration. We outline patterns for coordinating heterogeneous agents, text and real time, in process and remote via A2A, behind a single conversational voice. Attendees leave with concise design principles, key tradeoffs, and pitfalls to avoid when scaling from one voice to many minds.

Talk 2: Ole Bialas (Research Software Consultant at University of Bonn): What is "neural" about artificial neural networks? On the differences and similarities between artificial and biological intelligence

While, historically, the field of AI was strongly influenced by neuroscience and cognitive psychology, recent breakthroughs came predominantly from innovations in engineering. However, with traditional scaling laws seeing diminishing returns and models running out of new data to train on, the time seems particularly ripe to turn to neuroscience for inspiration. In my talk, I'll present recent research on similarities and differences between human brains and artificial neural networks. For example, deep networks trained on object recognition remarkably predict neural responses across the primate visual system, with different layers corresponding to different stages of cortical processing. Yet important differences remain: while both humans and ANNs learn to categorize images, humans organize categories primarily by semantic and functional relationships, whereas ANNs rely more heavily on perceptual similarity. These comparisons inevitably raise larger philosophical questions about intelligence and agency in biological organisms and artificial systems. While I won't be able to give conclusive answers, I hope to provide the audience with a new lens through which to view these questions.

👉 For directions, please follow this link or take a look at the uploaded images below.

We will share an agenda soon. See you in November,
Aaqib, Marc & Fabian

Artificial Intelligence
Machine Learning
Big Data
Data Science
Predictive Analytics

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